Mid-Senior Data Scientist (Forecasting & Pipelines)

Job Title: Mid-Senior Data Scientist (Forecasting & Pipelines)

Location: Remote – Latin America

Type of Contract: Full-Time | Contractor

Salary Range: Market Rates

Language Requirements: Fluent English

We are seeking a skilled Mid-Senior Data Scientist with strong expertise in forecasting and data pipeline development to join our growing team. You will play a key role in designing end-to-end machine learning workflows and architecting scalable data solutions in Snowflake. Your work will directly impact supply chain and retail decision-making by delivering accurate, production-ready forecasting models that drive operational efficiency and business growth.

Key Responsibilities

• Design, build, and maintain automated data pipelines and production-grade machine learning workflows.
• Develop and optimize demand and inventory forecasting models using advanced time-series and statistical techniques.
• Architect and manage large-scale datasets in Snowflake, ensuring high performance, reliability, and data integrity.
• Write complex, optimized SQL queries for data transformation and feature engineering.
• Translate supply chain and retail business requirements into scalable technical solutions and actionable insights.
• Implement best practices in code quality, documentation, testing, and statistical validation.
• Collaborate cross-functionally with business stakeholders and mentor junior team members when needed.

Must-Have Qualifications

• 4+ years of professional experience in Data Science or Machine Learning Engineering roles.
• Expert-level proficiency in Python (Pandas, NumPy, Scikit-learn, Prophet, Statsmodels, XGBoost or similar forecasting libraries).
• Advanced SQL skills with experience optimizing complex queries for analytics and ML workflows.
• Hands-on experience with Snowflake (experience with Snowpark or Tasks is a strong plus).
• Strong foundation in time-series analysis, statistical modeling, and working with large, messy datasets.
• Experience deploying scalable forecasting models into production environments.
• Bachelors or Masters degree in Computer Science, Statistics, Engineering, Economics, or a related quantitative field.

Preferred Qualifications

• Direct experience in Supply Chain (inventory optimization, logistics, replenishment planning) or Retail (demand planning, pricing, seasonality modeling).
• Experience with orchestration tools such as Airflow or Dagster.
• Exposure to MLOps practices, CI/CD pipelines, and model monitoring in production environments.
• Experience working in fast-paced, data-driven environments supporting operational teams.